Protein structure generation via folding diffusion
Published in Nature Communications, 2024
Recommended citation: Wu, K. E., Yang, K. K., van den Berg, R., Alamdari, S., Zou, J. Y., Lu, A. X., & Amini, A. P. (2024). Protein structure generation via folding diffusion. Nature Communications, 15(1), 1059. https://www.nature.com/articles/s41467-024-45051-2
Although novel deep learning methods like AlphaFold and OmegaFold excel at predicting the 3D structure of a protein given a sequence of amino acids, generating novel protein structures remains a tremendous challenge – one that if solved in generality, could lead to countless breakthroughs in protein-based therapeutics. We present a generative model of protein structure; we combine recent advances in diffusion models with a clever representation of protein structure to acheive state-of-the-art generative results.